Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Identifing the professional answerers with high probality in the social Q&A community can shorten the waiting time for users who ask questions to get satisfactory answers, promote knowledge sharing among users, and contribute to the sustainable and healthy development of the social Q&A community.[Method/process] Based on the social capital theory and motivation theory, this paper analyzed the motivation of users' answering questions, combined the expert discovery research to propose measurement indicators, and built a research model, then took Zhihu as a research example, and used Python to extract the eigenvalues and label of experimental data. Three common machine learning classification models, logistic regression model, random forest model and XGBoost model were used for training and prediction.[Result/conclusion] Compared with PageRank and HITS algorithms, the effectiveness and superiority of the method proposed by this paper have been verified. And this paper has provided a certain reference for the topic research of similar platforms such as healthy community problem push, expert identification and recommendation models.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] For e-commerce websites, the paper deeply analyzed the process of online review information quality perception, and clarified the operating rules and basic principles of online review information quality perception, which can contribute to analyze the mode of information processing and recognition for online reviews by users of information recipients comprehensively. [Method/process] The article started with the connotation and characteristics of information quality perception for online reviews, then it analyzed the four elements of online review information quality perception, clarified the five stages of the online review information quality perception process, and pointed out the two situational influencing factors in the information perception processing stage. A comprehensive analysis of the three types of pathways in the process of online review information quality perception is carried out as well. Finally, a model of online review information quality perception mechanism is constructed. [Result/conclusion] Information quality perception for online reviews is an orderly dynamic cyclic process. The constructed mechanism model can realize the overall grasp and understand of the information quality perception process for online reviews, providing theoretical and practical guidance for the research of information quality perception.
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